Anomalous Human Action Monitoring in Video Images Using RPCA-MFTSL AND PSO-CNN

Author:

Kumar S. Naveen,Rani R. Shoba

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Networks and Communications,Computer Graphics and Computer-Aided Design,Computational Theory and Mathematics,Artificial Intelligence,General Computer Science

Reference22 articles.

1. Franklin, R. J., &Dabbagol, V. (2020). Anomaly detection in videos for video surveillance applications using neural networks. In 2020 Fourth International Conference on Inventive Systems and Control (ICISC) pp. 632–637

2. Parameswaran S, Harguess J, Barngrover C, Shafer S, Reese M. Evaluation schemes for video and image anomaly detection algorithms. Autom Target Recogn. 2016;9844:98–109.

3. Chong YS, Tay YH. (2015). Modeling representation of videos for anomaly detection using deep learning: A review. arXiv preprint arXiv:1505.00523.

4. Zaidi S, Jagadeesh B, Sudheesh KV, Audre AA. (2017) Video anomaly detection and classification for human activity recognition. In 2017 International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC) (pp. 544–548). IEEE

5. Wang J, Xu Z. (2015). Crowd anomaly detection for automated video surveillance

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